The overarching hypothesis of Project 1 is that pet ownership is associated with exposure to a wider diversity of bacteria in house dust, and that these exposures profoundly influence the bacterial community composition (BCC) of the infant gastrointestinal microbiome, maturation of immune responsiveness and subsequently, the development of allergy and allergic asthma. This Project thus proposes two population based studies and a longitudinal panel study to shed light upon mechanisms that may explain the observed protective effects of exposure to household pets during infancy against development of atopy and high total IgE in infancy. We propose to use an advanced, highly sensitive and semi-quantitative method for bacterial detection, the G3 PhyloChip. This method offers an unprecedented capacity for detailed, high-resolution profiling of complex microbial communities, detecting in parallel common and uncommon members of assemblages present in house dust and infant stool samples. For Aims 1 and 2, we propose to examine samples already collected and stored from a large, carefully characterized, racially and socio-economically diverse, cohort of children (the WHEALS cohort). In Aim 1 we propose using an innovative case-cohort design to compare samples from infants who became atopic at age 2 years versus samples from a randomly selected sub-cohort (serving as the control group). Using the sub-cohort in Aim 2, we will determine whether, and in what fashion, bacterial community composition of both house dust and infant stool are impacted by pet-keeping and if they are related to each other. The study of bacteria, or bacterial communities, identified as deriving from dog keeping will be enabled by a small prospective panel study proposed as Aim 3, to analyze the changes in microbial community composition of house dust in child-occupied but previously pet free households into which a dog is introduced. Because the 16S-rRNAPhyloChip provides information on relative abundance of every bacterial taxon detected, we aim, through statistical analyses, to take advantage of this semi-quantitative data to identify particular bacterial species as critically important in protection against atopy development.